Multi-criteria decision-making for prioritizing photocatalytic processes followed by TiO2-MIL-53(Fe) characterization and application for diazinon removal

Multi-criteria decision-making (MCDM) can introduce the best option based on evidence. We integrated the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) to prioritize the alternatives for photocatalytic diazinon removal in a bench scale and characterized TiO2-MIL-53(Fe) for this purpose. Criteria and alternatives were listed based on systematic literature reviews and expert opinions. Then, AHP and TOPSIS questionnaires were developed and distributed to an expert panel for pairwise comparisons. We converted the linguistic variables into the corresponding fuzzy values and used R for mathematical calculations. Then, TiO2-MIL-53(Fe) was synthesized and characterized for diazinon removal under LED visible light. The AHP ranked criteria as availability > degradation efficiency > safety for the environment > material cost > energy consumption > mineralization efficiency > photocatalyst reusability > safety for personnel > equipment cost. Based on TOPSIS, the order of alternatives was TiO2-containing/Visible light > ZnO-containing/UV light > TiO2-containing/UV light > ZnO-containing/Visible light > WO3-containing/UV light. With a bandgap of 1.8 eV, TiO2-MIL-53(Fe) could remove 89.35% of diazinon at 10 mg/L diazinon concentration, 750 mg/L catalyst dose, pH 6.8, and 180-min reaction time. Hybrid AHP-TOPSIS identified the best option for photocatalytic diazinon removal from aqueous solutions. Thus, MCDM techniques can use systematic review results to overcome the uncertainty in designing experimental studies.


Materials and methods
This study was approved by the Research Ethics Committee of the Faculty of Health, Tehran University of Medical Sciences, Tehran, Iran, and followed the relevant guidelines and regulations. It was conducted in two phases. In phase I, an integrated AHP-TOPSIS was implemented to disclose the best photocatalytic system for diazinon removal. In phase II, experiments were carried out to determine the characteristics of the select photocatalyst and the efficacy of the photocatalytic system for diazinon removal.
Criteria and alternatives selection. Two authors (FBA and MD) conducted an extensive literature search to provide the research team with a preliminary list of criteria concerning the technical and managerial aspects of bench-scale photocatalysis. They had a history of dealing with the literature on photocatalytic diazinon removal, leading to a published systematic review 14 , implying their competencies. However, the research team was free to enrich the list with additional criteria based on their knowledge and experience. Finally, six criteria were selected based on the research team's opinions and the literature 18,19,23 , as follows: Process efficiency (sub-criteria: degradation efficiency and mineralization efficiency), process cost (sub-criteria: material cost and equipment cost), availability, photocatalyst reusability, energy consumption, and process safety (sub-criteria: personnel and the environment). These criteria were employed to appraise the most widely used photocatalytic systems in the experimental studies retrieved from our systematic review of 777 articles published in the recent 5 years with a sound methodology described elsewhere 14 . We categorized the alternatives based on the photocatalyst and light source as follows: TiO 2  www.nature.com/scientificreports/ containing/UV light, and WO 3 -containing/UV light. Finally, a hierarchy diagram was drawn according to the criteria/sub-criteria and alternatives, as shown in Fig. S1.
Expert panel establishment. Expert panels are widely used for weighing criteria and evaluating alternatives in MCDM techniques 28 . The expert panel in this study included 18 Ph.D. holders in Environmental Health Engineering with an experience in photocatalytic removal of persistent pollutants. They were purposefully selected from different universities across Iran. Due to COVID-19 limitations, they were contacted via emails to be briefed about the study procedure and provided with AHP and TOPSIS questionnaires. Giving informed consent to participate was a prerequisite for recruiting panel members.
Fuzzy AHP running. A questionnaire was designed for running AHP in three parts. The first part introduced the objectives, criteria, and the procedure to the expert panel. The second part comprised the pairwise comparisons of criteria and sub-criteria. In this part, each criterion/sub-criterion was compared with its pairs concerning their importance in selecting an alternative for the photocatalytic removal of diazinon in the bench scale. The third part included a fact sheet derived from reliable literature, presenting the current knowledge about criteria and sub-criteria to help the expert panel fill out the questionnaire. To do so, the expert panel members applied linguistic variables that were then converted into their corresponding fuzzy values based on the Delphi method 29 , as shown in Table S1. Next, a matrix was developed for each completed questionnaire. The obtained matrices were checked for consistency of judgments based on the method presented by Mohamed Salah-eldin 30 . In this method, an inconsistency index was calculated for each matrix. Consistent matrices were those with an inconsistency index of ≤ 0.1 and were utilized to calculate the fuzzy weight of each criterion/subcriterion through the geometric mean method using fuzzy AHP package version 0.9.0 in R software. Then, the Best Non-Fuzzy Performance (BNP) values were computed to rank the criteria. At the end of the AHP, a weight was assigned to each criterion/sub-criterion and used for fuzzy TOPSIS calculations.
Fuzzy TOPSIS running. In this step, another questionnaire was designed to ask the experts' opinions about the available alternatives relative to each other concerning each criterion/sub-criterion. The first part explained the purpose of the questionnaire and its procedure. Besides, the raters were provided with a fact sheet about alternatives respecting the criteria. This information was obtained from a literature search, as described elsewhere 14 .
In the next part, a table of alternatives versus criteria/sub-criteria was developed, and the expert panel was asked to use linguistic variables to rate each alternative relative to others (Table S2). Only experts with consistent AHP matrices were invited to fill out the TOPSIS questionnaires in this step. The experts were trained to value the alternatives based on their knowledge, experience, and the literature data we provided as the fact sheet. Besides, they were instructed to judge only the given catalysts as pristine regardless of various, endless modifications applicable to change the photocatalyst characteristics for various reasons. The linguistic variables were converted into fuzzy values in the next step, and a fuzzy matrix was created for each questionnaire. All matrices were integrated into a unit matrix, called the "aggregate fuzzy decision matrix." The aggregate matrix was normalized in the next step to rescale the values from 0 to 1. For normalization, each fuzzy value in a triangular fuzzy set was divided by the maximum upper bound value for each criterion, as described elsewhere 26 . Then, all normalized fuzzy values in the matrix were multiplied by their fuzzy weights attained from the fuzzy AHP. Therefore, a weighted normalized fuzzy decision matrix was created. Next, the Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS) were calculated to quantify the distance of each alternative from the ideal solutions represented as positive and negative ideal solutions (d + and d − , respectively). Finally, the Closeness Coefficient (CCi) and Normalized CCi (NCCi) were calculated for each alternative and used for ranking. Indeed, the CCi measured the distance of each alternative from FPIS. The best alternative had the highest CCi and an NCCi closer to unity 31 . Experimentation. The select photocatalytic process from the AHP-TOPSIS technique, i.e., TiO 2 -containing/ Visible light, was practiced for diazinon removal from aqueous solutions. We fabricated a TiO 2 -MIL-53(Fe) composite, which has never been employed for diazinon removal, by combining the methods described by Zhang et al. 32 and Zhang et al. 33 to use in the presence of LED visible light. Briefly, 170 mg TiO 2 (anatase, Merck, Germany) was added to the mixture of 24 mL DMF (99.8%, Merck, Germany) and 2 mL absolute ethanol (Romil, UK). After 30 min ultrasonication (Elm sonic S30H, Elma Schmidbauer GmbH, Singen, Germany), 0.332 g H 2 BDC (98%, Merck, Germany) and 0.27 g FeCl 3 ·6H 2 O (Merck, Germany) were added under vigorous mixing for 30 min. Then, the whole mixture was placed in a Teflon-lined stainless-steel autoclave (60 mL) at 150 °C for 15 h. The product was washed several times using DMF and ethanol and dried in 150 °C for 12 h.
A Field Emission Scanning Electron Microscopy device (FESEM; TESCAN BRNO-Mira3 LMU, Czech Republic) coupled with energy dispersive X-ray spectroscopy (EDS) determined the photocatalyst's morphology and elemental composition. A UV-visible spectrophotometer (Shimadzu UV-160A, Japan) was utilized to determine the optical properties of the photocatalyst in a wide range of wavelengths. The data were used to draw Tauc plots and calculate the band gap of the photocatalysts. Photoluminescence (PL) spectra were used to determine the recombination rate using a Varian Cary Eclipse Fluorescence Spectrophotometer (Agilent Co., USA) equipped with a xenon lamp at the excitation wavelength of 300 nm. Moreover, Mott-Schottky analysis was performed at a 500 Hz frequency in 0.1 M Na 2 SO 4 solution (pH = 6.8) to determine the flat band potential and shed light on reaction mechanisms. The X-ray diffraction analysis was conducted to determine the structure of the fresh and recycled photocatalyst in a 2θ range of 1°-80° (XRD Explorer, GNR, Italy; Dectris detector; Tube Cu Kα = 1.54 Å, Voltage 40 kV, and Current 30 mA). www.nature.com/scientificreports/ The photocatalyst experiments were conducted at a photocatalyst dose of 750 mg/L, diazinon concentration of 10 mg/L, solution pH of 6.8, and irradiation duration of 180 min. A 30-min reaction time was allowed in the dark before irradiation to compensate for the adsorption effect on photocatalysis efficacy. Adsorption and photolysis experiments were performed for the same duration without light and photocatalyst, respectively. The photocatalyst was employed in three successive experiments after regeneration for reusability assessment. Then, removal efficiencies were compared across the cycles.
A batch reactor made of glass was utilized with a total volume of 100 mL. A 50 mL working volume was employed and constantly agitated at 250 rpm during reactions on a magnetic stirrer. Irradiation was performed with two COB LED lamps (50 W power each) emitting visible light above 380 nm. Each lamp was fixed at a distance of 1 cm from each side of the vessel. The diazinon concentration in the initial and final solutions was determined with an HPLC apparatus (Knauer Smartline, Germany) equipped with a UV/Visible detector (set at 250 nm) and a separation column (C18, 150 mm × 4.6 mm). The methanol-to-water volumetric ratio of 80/20 at a flow rate of 1.2 ml/min was used for the mobile phase. The removal efficiency was computed using Eq. (1): where R is the removal efficiency (%), C i is the initial diazinon concentration (mg/L), and C f is the final diazinon concentration (mg/L).

Results and discussion
We identified six criteria for the appraisal of bench-scale photocatalytic techniques, including process efficiency (degradation and mineralization), process cost (material and equipment), availability, photocatalyst reusability, energy consumption, and safety (personnel and the environment). The alternatives found in the literature for photocatalytic diazinon removal were TiO 2 -containing/Visible light, TiO 2 -containing/UV light, ZnO-containing/ Visible light, ZnO-containing/UV light, and WO 3 -containing/UV light.
Fuzzy AHP-TOPSIS results. An expert panel of 18 members was established to make pairwise comparisons between criteria/sub-criteria using linguistic variables. Then, a matrix was developed for each response (n = 18), with inconsistency indices of 0.05-0.4. After removing inconsistent matrices (n = 7), the remaining ones (n = 11) with ≤ 0.1 inconsistency indices were used for calculating the fuzzy weight of criteria/sub-criteria through the geometric mean method. This method generated the integrated matrices for criteria (Table S3) and sub-criteria (Table S4). The integrated matrix of criteria had a consistency ratio of 0.005. Table 1 shows that the BNP fractions were 0.231 for efficiency, 0.208 for safety, 0.201 for costs, 0.150 for availability, 0.120 for energy consumption, and 0.083 for photocatalyst reusability. Concerning sub-criteria, degradation efficiency was superior to mineralization efficiency, material cost to equipment cost, and environmental safety to personnel safety. Respecting the individual BNP values, the order of importance was as follows: Availability > degradation efficiency > safety for the environment > material cost > energy consumption > mineralization efficiency > photocatalyst reusability > safety for personnel > equipment cost. In a similar study, Azari et al. 34 utilized integrated fuzzy AHP-TOPSIS for prioritizing dye removal processes using carbon-based adsorbents. They showed accessibility as the most important appraisal criterion, followed by reusability, adsorption capacity, environmental safety, human safety, material cost, and equipment cost, with BNP values in the range of 0.049-0.250. www.nature.com/scientificreports/ The criteria weights emerging from the fuzzy AHP were used to complete the fuzzy TOPSIS. Eleven eligible experts completed the TOPSIS questionnaires. The aggregate fuzzy decision matrix is given in Table S5, and its normalized matrix is shown in Table S6. A weighted normalized fuzzy decision matrix was created after applying the criteria weights obtained from fuzzy AHP, as summarized in Table S7. Then, the distances from positive and negative ideal solutions (d + and d − , respectively) were measured for each alternative, followed by CCi and NCCi calculations. Table 2 demonstrates the final results of fuzzy TOPSIS and the ranking of alternatives based on NCCi. As can be seen, the preference order of the alternatives was as follows: TiO 2 -containing/Visible light > ZnO-containing/UV light > TiO 2 -containing/UV light > ZnO-containing/Visible light > WO3-containing/ UV light. Therefore, in the framework of this study, we identified TiO 2 -containing/Visible light as the best photocatalysis system for diazinon removal. Based on the NCCi values of 0.1124-0.1395, Azari et al. 34 ranked carbonbased adsorbents for dye removal as follows: powdered activated carbon > granular activated carbon > carbon nanotubes > graphene oxide > graphene > reduced graphene oxide > graphite > coal.
With a molecular weight of 79.87 g/mol, TiO 2 is a traditional photocatalyst used in the experimental removal of persistent pollutants. It is a readily available material with an easy application 35 . Thus, it gains a high score on availability. However, TiO 2 has a wide band gap (3.2 eV, as obtained in this study), making it only active at wavelengths below 385 nm 36 . Therefore, it must be modified before applying in the visible light spectrum. Studies have shown that modified TiO 2 can be highly efficient under visible light and completely remove diazinon. For example, Nakaoka et al. 37 utilized Pt-doped TiO 2 in the presence of a 900 W xenon lamp and achieved 100% diazinon removal. Zangeneh et al. 38 and Molla et al. 39 also reported comparable results.
Concerning safety for the environment, photocatalysts used for water and wastewater technologies are often inert nanoparticles that impose no extra hazard to the environment; besides, they must be safe for biological systems and have low toxicity [40][41][42] . TiO 2 is no exception; its 96 h-LC50 has been measured as > 1000 mg/L for fish, and its 48 h-EC50 has been reported as > 1000 mg/L for Daphnia magna. According to the TiO 2 Material Safety Data Sheet in the literature, it is also readily degradable in the environment. Besides, TiO 2 can be prepared at a low cost, as titanium is naturally found in the earth's crust with an abundance of 0.44% 43 . In the laboratory, it can be produced by several facile methods, including hydrothermal, solvothermal, sol-gel, chemical precipitation, electrodeposition, direct oxidation, sonochemical, and microwave methods 44 . These methods necessitate the use of precursors such as titanium tetra-ethoxide Ti(OEt) 4 , titanium tetra-isopropoxide Ti(OPr i ) 4 , titanium ethoxide Ti(OC 2 H 5 ), titanium isopropoxide Ti(OC 3 H 7 ) 4 , titanyl sulfate TiOSO 4 , titanium tetrachloride TiCl 4 , and titanium trichloride TiCl 3 45 . Moreover, quality-grade TiO 2 powder is readily available for laboratory experiments from Sigma Aldrich and Merck suppliers with reasonable costs for research purposes.
Energy consumption in photocatalysis largely depends on the characteristics of the light source for irradiation, including electrical current intensity and working voltage, critical factors for operating costs. The Electrical Energy per Order (E EO ) is usually expressed as a measure of energy consumption in photocatalytic processes to tradeoff between cost and effectiveness. E EO is the amount of electrical energy (kWh) needed for one order of magnitude reduction of pollutant concentration in the unit volume of solution. Therefore, it is proportional to the power of the light source and the irradiation duration to reach a 90% removal rate. Although the E EO of various photocatalytic technologies was reported from 38.93 46 to 350.36 kWh/m 3 47 , the literature lacked this data concerning diazinon removal with TiO 2 -containing/Visible light, which needs to be elucidated in future studies.
The mineralization efficiency concerns the complete oxidation of organic carbon to inorganic carbon, CO 2 . Therefore, it requires measuring the total organic content of the aqueous solution before and after photocatalysis. A mineralization efficiency close to 100% indicates fewer organic by-products to be concerned about, as research indicated that some by-products are more toxic than their parental compounds 48 . The mineralization reaction for diazinon mineralization is proposed as follows 37 : The literature has reported the mineralization efficiency of TiO 2 -containing/Visible light processes between 63 49 and 100% 38 . The latter was obtained in the presence of B/TiO 2 -SiO 2 /CoFe 2 O 4 as the catalyst and 18 W fluorescent lamps as the light source.
The photocatalyst reusability can be a significant factor in the economy of photocatalysis, as the photocatalyst is usually a precious material and is required in large amounts of up to 600 mg/L in optimum conditions 14 . In experiments, reusability is measured by successively using the regenerated photocatalyst under the same experimental conditions and then comparing the removal efficiencies across the cycles. The regenerated photocatalyst should show an efficiency close to that of the fresh one. TiO 2 catalysts are usually accompanied by good reusability characteristics. A study 50 incorporated TiO 2 into palladium heterogeneous catalysts to improve its reusability. Reusability can also pinpoint the stability feature, as unstable photocatalysts can release their ingredients into the www.nature.com/scientificreports/ solution, leading to secondary contamination. Salarian et al. 49 and Zangeneh et al. 38 claimed negligible decreases in diazinon removal efficiency after seven and three cycles of TiO 2 -containing/Visible light photocatalysis from 85 to 80% and 100 to 96%, respectively. Concerning personnel safety, working in the laboratory cannot be without risks to the staff and examiners. In photocatalysis, the risks may root in contact with chemicals and exposure to light. Based on the United Nations' Globally Harmonized System (GHS), TiO 2 is a probable carcinogen, placed in category 2 of carcinogens. Therefore, it must be avoided from any contact with any concentration. However, USEPA recognizes it as a source of low concern based on experimental and modeled studies 51 . Photocatalytic systems utilizing UV radiation pose additional risks to people, as UV exerts high-energy photons harmful to body organs, including the eyes and skin. Ultraviolet is a probable carcinogen to the skin 52 and an eye irritant 53 , depending on exposure duration, light intensity and wavelength, and distance from the source 54 . Therefore, concerning safety regulations, lowenergy visible light might be advantageous over UV light. However, recent research has postulated a role for high-intensity visible light, as is usual for photocatalysis, in skin damage symptoms such as hyperpigmentation 55 .
Here, we referred to the light source costs as the equipment cost for photocatalysis to distinguish between UV and visible light sources. This criterion had the least relevance to selecting photocatalytic processes in our study. Lamps are available at various prices depending on their light-emitting mechanisms. Costly mercury lamps are the traditional options for UV light generation, while sunlight is free for having visible light necessary for activating the photocatalyst. In recent years, the advancement in Light-Emitting Diodes (LEDs) technology has made them attractive for irradiation. LED lamps need small installation spaces, have high energy efficiencies, and are much less costly. Although they can emit a broad light spectrum from UV to visible, they have been less utilized for photocatalysis than mercury lamps for UV light and xenon lamps for visible light. Owing to their unique characteristics, they can open a new window for researchers to remove persistent pollutants more cost-effectively.

Characteristics of the select photocatalyst.
Based on the fuzzy AHP-TOPSIS results and in the framework of this study, the TiO 2 -containing/Visible light photocatalytic process emerged as the best alternative for diazinon removal from aqueous solutions. Therefore, this process was utilized in a set of experiments to determine its efficiency. As known, TiO 2 is a semiconductor that needs modification to be activated in visible light. In this study, we fabricated a TiO 2 -MIL-53(Fe) composite. Figure 1 demonstrates the SEM images of TiO 2 -MIL-53(Fe) at different magnifications to present the morphology of the as-prepared photocatalyst. Based on the image, TiO 2 nanoparticles were successfully incorporated into the metal-organic framework structure. TiO 2 nanoparticles surrounded the rod-like MIL-53(Fe) particles to make a rough surface. Figure S2 demonstrates the EDS plots and compositional analysis of TiO 2 , MIL-53(Fe), and TiO 2 -MIL-53(Fe). As can be seen, the composite consisted of Ti (18.90%), C (37.18%), O (41.78%), and Fe (2.14%). These results corroborate the findings of Zhang et al. 33 , in which the synthesized MIL-53(Fe) gradually lost its polyhedron shape as it was incorporated with different amounts of TiO 2 . In the EDS spectra, they detected C, O, Fe, and Ti elements at percentages proportional to the added amounts of TiO 2 precursor. PL spectra in Fig. 3 show a large peak for TiO 2 , indicating a high electron-hole recombination rate. The difference between the peak intensity of MIL-53(Fe) and TiO 2 -MIL-53(Fe) shows the longer life of electron-hole pairs www.nature.com/scientificreports/ on the modified photocatalyst. So, it can be inferred that TiO 2 -MIL-53-(Fe) composite has a higher separation efficiency and charge lifetime 33,56 . Figure 4 demonstrates the Mott-Schottky plots of TiO 2 -MIL-53(Fe) and MIL-53(Fe). The flat band potential (V fb ) was measured using this graph. As can be seen, both photocatalysts are n-type due to the positive slope of the curves 56 . In the case of TiO 2 -MIL-53(Fe), the conduction band potential (E CB ) and valance band potential (E VB ) are calculated as − 0.825 V and 0.975 V versus NHE, respectively. The V fb of MIL-53(Fe) is − 0.975 V versus Ag/AgCl at pH 6.8. It should be noted that the conduction band in n-type photocatalysts is very close to V fb . Therefore, E CB is − 0.775 V versus NHE. On the other hand, E VB can be calculated through the difference between the band gap value (E g ) and E CB 33 . Thus, regarding the MIL-53(Fe) band gap, which was measured as 1.8 eV in this study, E VB is calculated as 0.975 V versus NHE. As shown earlier, the band gap of TiO 2 was 3.2 eV. Moreover, according to the literature 57 , E CB and E VB of TiO 2 are − 0.4 V and 2.8 V versus NHE, respectively. Due to the position of CB in MIL-53(Fe) and TiO 2 , photogenerated electrons can transfer onto the CB of TiO 2 . On the other hand, positive holes produced on TiO 2 can migrate onto the VB of MIL-53(Fe), reducing recombination and improving efficiency 33,56,57 . The obtained data were utilized to elucidate the mechanism of photocatalyst activation. Figure 5 demonstrates the graphical representations of the activation mechanism and charge transfer route of TiO 2 -MIL-53(Fe).
These results proved the efficacy of TiO 2 -MIL-53(Fe)/Visible light for diazinon abatement. The results showed that the as-prepared catalyst could remove diazinon via adsorption and oxidation mechanisms. However, its          58 indicated a poor photocatalytic performance for MIL-53(Fe) because of the fast recombination of electron-hole pairs. They overcame this problem by adding persulfate as an electron acceptor and obtained around 100% removal of acid orange 7 after 90 min of LED irradiation at the intensity of 0.47 mW/cm 2 . Figure 7 depicts the data on the reusability and stability of TiO 2 -MIL-53(Fe). As the figure inset shows, the diazinon removal rate decreased from 89.35 to 85.8% after three cycles of photocatalyst reuse. The slight reduction in removal efficiency can be due to the loss of photocatalyst active sites during photocatalysis and regeneration. Moreover, the XRD patterns of the fresh and (three-cycle) reused TiO 2 -MIL-53(Fe) photocatalyst show the same peak patterns, confirming that the crystallized structure of TiO 2 -MIL-53(Fe) was not destroyed after three cycles of regeneration and reuse. In the XRD spectra, there are some distinctive peaks at 2θ of 9.31° and 12.61°, which agree with the previous study 33,59 . In addition, three other peaks at 2θ = 25.35°, 37.87°, and 48.13° could relate to the anatase structure of TiO 2 , corresponding to (101), (004), and (200) crystal planes, respectively 33,59,60 .

Conclusion
In this study, based on fuzzy AHP-TOPSIS, availability emerged as the most important criterion for selecting photocatalysis systems, and TiO 2 -containing/Visible light was the best solution to implement in bench-scale studies of diazinon removal. We fabricated a TiO 2 -MIL-53(Fe) composite with a band gap of 1.8 eV and a low electron-hole recombination rate, which could remove diazinon at 89.35% after 180 min irradiation under LED visible light. However, we need more studies to optimize the conditions to improve the removal rate and shed light on other aspects of TiO 2 -MIL-53(Fe)/Visible light application, including mineralization efficiency and costs. As a limitation of the study, the alternatives were evaluated based on the experts' knowledge, experience, and local conditions, making the results not generalizable. Also, we found very few similar studies in the literature to compare the results for adequate discussion. Nevertheless, we demonstrated that MCDM techniques could be employed to select the best treatment alternative in the literature before designing experimental studies. Thus, researchers can integrate MCDM techniques into their systematic reviews to overcome the uncertainty in choosing a technology and design their original studies based on available evidence.

Data availability
All data used in this article are available for everyone upon reasonable request. To request the data from this study, you can contact Fatemeh.barjasteh@gmail.com.